基于片段组装的蛋白质结构预测方法综述
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浙江工业大学信息工程学院, 杭州 310012

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国家自然科学基金(61773346)资助项目;浙江省自然科学基金重点项目(LZ20F030002)资助项目。


Review of Protein Structure Prediction Methods Based on Fragment Assembly
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College of Information Engineering, Zhejiang University of Technology, Hangzhou 310012, China

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    摘要:

    蛋白质三维结构决定了其特殊的生物功能,蛋白质三维结构对蛋白质功能研究、疾病的诊断与治疗、创新药物研发都有着重要的科学意义。利用计算机技术从氨基酸序列预测蛋白质三维结构是获取蛋白质三维结构的有效方法。片段组装是一种广泛采用的蛋白质结构预测技术,它将连续的构象空间优化问题转换成离散的实验片段组合优化问题,从而有效地减小了构象搜索空间。首先介绍了片段组装技术;其次总结了基于片段组装的蛋白质结构预测的发展历程,并对部分具有代表性的方法进行了简要阐述;然后介绍了蛋白质结构预测研究中常用的数据库和评价指标,并比较了不同预测方法的性能;最后分析并指出了当前基于片段组装的蛋白质结构预测方法所存在的挑战性问题,并对该领域未来的研究方向进行了展望。

    Abstract:

    The 3D structure of protein determines its special biological function. The 3D structure of protein has important scientific significance for protein function research, disease diagnosis and treatment, and innovative drug research and development. It is an effective method to predict protein 3D structure from amino acid sequence by computer. Fragment assembly is a widely used technique for protein structure prediction, which can effectively reduce the conformational search space by converting continuous conformational space optimization into discrete experimental fragment combination optimization. This paper first introduces the technology of fragment assembly. Next, the development of protein structure prediction based on fragment assembly is summarized, and some typical prediction methods are briefly described. The commonly used databases and evaluation indexes in protein structure prediction are then demonstrated, and the performance of the representative prediction methods is compared. Finally, we analyse and point out the challenges of the current protein structure prediction methods based on fragment assembly, and look forward to the future research directions in this field.

    表 6 Table 6 Experimental conditions for analysis of SAE network
    表 4 Table 4 Icing conditions for analysis of SAE network
    表 2 MMpred和Rosetta-d (距离约束的Rosetta)在320个基准测试蛋白上的平均预测结果[36]Table 2 Average prediction results of MMpred and Rosetta-d (Rosetta with distance constraints) on 320 benchmark proteins[36]
    表 5 Table 5 Comparison of ice shape consistency indexes
    图1 片段组装示意图Fig.1 Schematic diagram of fragment assembly
    Fig.
    图1 Water collection efficiency comparison between computed result and experimental data at different conditionsFig.1
    图2 Ice shape comparison between the computed result and experimental data at different conditionsFig.2
    图3 Ice shape parameters defined in the SAE standard[15]Fig.3
    图4 DBN network structureFig.4
    图5 SAE network structureFig.5
    图7 Comparison of ice shape between the SAE prediction and the icing wind tunnel experimental resultsFig.7
    表 1 CGLFold、C-QURK、MULTICOM_CLUSTER、BAKER-ROSETTASERVER和RaptorX-Contact在14个CASP13的FM目标上的预测结果比较[10]Table 1 Prediction results comparison of CGLFold, C-QUARK, MULTICOM _CLUSTER, BAKER-ROSETTASERVER, and RaptorX-Contact on the 14 FM targets of CASP13[10]
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张贵军,刘俊,赵凯龙.基于片段组装的蛋白质结构预测方法综述[J].数据采集与处理,2021,36(4):629-638

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  • 收稿日期:2021-05-14
  • 最后修改日期:2021-07-01
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  • 在线发布日期: 2021-09-23